{"id":"W1942170672","doi":"10.1109/vetec.1997.605833","title":"Adaptive filtering based DS/SS code acquisition in frequency selective and flat Rayleigh fading channels","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Fading; Rayleigh fading; Degradation (telecommunications); Electronic engineering; Fading distribution; Matched filter; Computer science; Rayleigh scattering; Filter (signal processing); Telecommunications; Physics; Channel (broadcasting); Engineering; Optics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004401908,0.0003743312,0.0002641182,0.0003429255,0.0002634364,0.0003084939,0.0002049616,0.0003871447,0.0006572348],"category_scores_gemma":[0.001706849,0.000124169,0.0001365509,0.0002957647,0.0003178377,0.0003380442,0.0002064069,0.0002140481,0.0001536796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004081131,"about_ca_system_score_gemma":0.0003721015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002578185,"about_ca_topic_score_gemma":0.002493836,"domain_scores_codex":[0.9997104,0.0000702816,0.00001346552,0.00003525293,0.0001087556,0.00006175433],"domain_scores_gemma":[0.9989122,0.0005920768,0.0001355956,0.00006182254,0.0002540615,0.00004414539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004318811,0.0001757846,0.0111664,0.0001650834,0.0001061391,0.000552229,0.000232389,0.2848082,0.5083624,0.006852895,0.0005705759,0.1826891],"study_design_scores_gemma":[0.00005848973,0.0008150385,0.006902575,0.00001071258,0.00005427533,0.0005186269,0.00004706285,0.820776,0.1691106,0.0009934714,0.0006785002,0.00003462069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8963382,0.0002982464,0.1015388,0.00005982366,0.00002031225,0.00002634051,0.00003344851,0.0002589125,0.001425838],"genre_scores_gemma":[0.9864829,0.0001167041,0.01274463,0.00001254593,0.000008652066,0.000008790739,0.00002724788,0.000008502298,0.000590041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002578185,"threshold_uncertainty_score":0.005126357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05102419984461787,"score_gpt":0.2740742042113986,"score_spread":0.2230500043667807,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}